Healthcare Jobs in Lisbon, Portugal (Now Hiring) — 222 open — Page 5

Are you ready to define how AI safely scales across a global enterprise so patients receive medicines reliably and at speed? In this role, you will build the guardrails and operating model that enable responsible AI in commercial decision-making, driving measurable value while protecting our license to operate.

Sitting at the intersection of AI, risk, and operating model design, you will translate evolving regulation and ethics into pragmatic standards that teams adopt willingly. You will turn pilots into a governed, value-focused portfolio, elevate data readiness, and grow AI literacy so innovators move faster without compromising on safety or trust. Join us to balance pace with responsibility and help leaders make confident, compliant decisions about AI.

Accountabilities:

• AI governance framework: Design and maintain a fit-for-purpose governance model that enables safe, compliant, and scalable AI adoption. Define standards, controls, approval processes and lifecycle requirements; publish playbooks and operating procedures; scan and validate agents against standards to enable rapid yet responsible deployment.
• Risk management and compliance: Coordinate AI risk assessments and ensure audit readiness. Monitor regulatory and policy requirements; align with enterprise AI standards; partner closely with Legal, Compliance, Security and Data Privacy so new use cases meet obligations from day one.
• Responsible AI: Define principles tailored to our context and embed them in ways of working. Monitor bias, transparency, explainability and control requirements; ensure human oversight for higher-risk use cases; lead governance reviews for new initiatives to protect users and patients.
• AI portfolio management: Establish and maintain a single inventory of tools, agents, automations and use cases. Govern demand intake and prioritisation; track deployment status, ownership and value; manage the AI asset lifecycle so investments deliver enterprise benefit.
• Data and knowledge readiness: Set standards for data quality and knowledge management. Ensure solutions use trusted business content; govern training data, prompts and repositories to reduce model risk and increase reproducibility.
• Adoption and capability building: Build and execute a learning strategy that raises fluency at all levels. Lead communities of practice and champion networks; share best practices; drive behaviour change so AI-enabled ways of working stick.
• Monitoring and continuous improvement: Define governance KPIs and run effectiveness reviews. Manage audits; identify gaps; iterate standards and processes to keep pace with technology and regulation.
• Strategic leadership and influence: Shape the AI strategy for this function and connect it to enterprise transformation priorities. Operate with autonomy, influence senior stakeholders without direct authority, and make clear recommendations that balance value, risk, compliance and adoption.
• Outcomes and impact: Increase governance compliance rates, reduce risk exposure, raise AI adoption maturity, improve AI inventory completeness and audit outcomes, and uplift training and capability metrics—progressing from immediate framework establishment to sustained enterprise-scale value.

Essential skills and experience:

• AI governance expertise, including policy design, control frameworks, approval processes, lifecycle management, and governance operating procedures.
• Responsible AI judgement, including the ability to identify and manage risks related to bias, explainability, transparency, human oversight, accountability, and unintended consequences.
• Risk and compliance capability, including AI risk assessment, audit readiness, regulatory awareness, data privacy considerations, security alignment, and enterprise policy adherence.
• Operating model design skills to define ownership, decision rights, support models, escalation paths, demand intake, prioritisation, and portfolio governance.
• AI portfolio management skills, including maintaining inventories of agents, tools, automations, use cases, deployment status, ownership, value, and risk profile.
• Data and knowledge management skills, including standards for trusted content, knowledge repositories, prompt libraries, data quality, and content lifecycle controls.
• Adoption and capability-building skills, including learning strategy, community management, training design, champion networks, communication planning, and behaviour change.
• Strong cross-functional influence across Procurement, IT, Legal, Compliance, Data Privacy, Security, Risk, and business leadership to balance innovation speed with responsible scaling.

Desirable skills and experience:

• Experience applying global AI regulations and standards (for example, EU AI Act readiness, NIST AI RMF, ISO/IEC AI management systems) in a complex, regulated environment.
• Track record implementing agentic AI in enterprise workflows, including human-in-the-loop controls and monitoring at scale.
• Background in strategic sourcing, supplier risk, or commercial operations within life sciences or other highly regulated industries.
• Advanced degree in a relevant field (data science, law/ethics, information systems, or business) or equivalent experience.
• Professional certifications related to AI governance, risk, privacy, or security.
• Demonstrated success building executive governance forums and measurable adoption programs across global teams.

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Why AstraZeneca:
Here, bold science meets pragmatic execution. You will work with world-class experts across disciplines to turn breakthrough ideas into governed, scalable AI that accelerates how we discover, make and deliver medicines. We invest in modern technology and encourage unconventional combinations of talent to spark better solutions, while valuing kindness alongside ambition. Your impact will be visible—from safer decisions and stronger supplier partnerships to more resilient supply for patients—backed by a culture that expects you to lead, supports you to learn, and gives you the platform to influence at enterprise scale.

So, what’s next?
Step into this pivotal role and shape how responsible AI unlocks value at scale—build the standards, grow capability, and leave a legacy of safer, faster decisions that ultimately reach patients sooner. Apply today.

Date Posted

28-Jul-2026

Closing Date

15-Aug-2026

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.